tabby VS codellama

NixOS just got tabbyml[1] which is built on llama-cpp. Working on systemsd services the weekend and updating latest tabbyml release which supports rocm in addition to cuda

[1] https://github.com/TabbyML/tabby

[2] https://github.com/NixOS/nixpkgs/pull/291744

Nice implementation! It should serve as a great reference for a minimal Tabby's backend API. Thank you for sharing it!

Yeah - ultimately, it won't be as performant or feature-rich compared to https://github.com/TabbyML/tabby, but it's still perfect for educational purposes!

Looks interesting! What are the main differences between this and https://github.com/TabbyML/tabby ?

TabbyML | Software Engineer (Rust) | REMOTE

Self-hosted AI coding assistant. An opensource / on-prem alternative to GitHub Copilot.

Project: https://github.com/TabbyML/tabby

Tabby is seeking a Software Engineer proficient in Rust to join our core engineering team. In this role, you will be responsible for developing the following features:

There are a bunch of VSCode extensions that make use of local models. Tabby seems to be the most friendly right now, but I admittedly haven't tried it myself: https://tabbyml.github.io/tabby/

Check out https://github.com/TabbyML/tabby, which is fully self-hostable and comes with niche features. On M1/M2, it offers a convenient single binary deployment, thanks to Rust. You can find the latest release at https://github.com/TabbyML/tabby/releases/tag/latest.

(Disclaimer: I am the author)

The github [0] hasn't been fully updated, but it links to a paper [1] that describes how the smaller code llama models were trained. It would be a good guess that this model is similar.

[0] https://github.com/facebookresearch/codellama

This k8s application deploys an instance of Voyager along with a Fabric Minecraft server with required fabric mods. It assumes you have a local deployment of a Large Language Model (LLM) with 4K-8K token context length with a compatible OpenAI API, including embeddings support.

I have been playing with code Llama (the 7B python one). It does pretty well, but I don't understand what the parameters in the code mean and how I should modify them to work best on my hardware. I'm looking at the code in: https://github.com/facebookresearch/codellama/blob/main/llama/generation.py.

Should I use HuggingFace https://huggingface.co/codellama/CodeLlama-34b-hf or grab the model from Facebook https://github.com/facebookresearch/codellama?

such rights.

https://github.com/facebookresearch/codellama/blob/main/LICE...

https://github.com/facebookresearch/llama/blob/main/LICENSE

Bringing AI to the coding community: Code Llama is designed to support software engineers across sectors – including research, industry, and open-source projects. You can checkout the Github repo here.

GIthub https://github.com/facebookresearch/codellama